Objective: To address the challenges in human-robot interaction control for lower-limb rehabilitation exoskeletons by optimizing gait pattern design and compliance control strategies, thereby enhancing the safety, comfort, and precision of rehabilitation training. Methods: Rhythmic dynamic movement primitives were utilized to generate personalized gait trajectories, combined with an admittance control strategy to design a trajectory tracking controller. This controller adjusts control parameters in real-time to guide the user’s gait towards the desired trajectory, reduce interaction torque, improve gait consistency, and ensure safety and effectiveness during rehabilitation training. Results: Walking experiments with three participants using the lower-limb rehabilitation exoskeleton demonstrated that, compared to transparent mode, the trajectory tracking mode reduced the root mean square error (RMSE) of hip and knee joint angle trajectories from 7.24° and 13.25° to 3.01° and 4.76°, respectively. The mean absolute error (MAE) decreased from 6.35° and 11.17° to 2.54° and 3.50°, respectively. The absolute mean interaction torque decreased from 3.55 Nm and 3.42 Nm to 2.80 Nm and 1.86 Nm. These results validated that the trajectory tracking controller significantly improves gait consistency and comfort. Conclusion: The application of rhythmic dynamic movement primitives combined with compliance control strategies in lower-limb rehabilitation exoskeletons shows great potential. It effectively enhances the precision and comfort of rehabilitation training, providing patients with a safer and more personalized rehabilitation experience.